• Annual Conference of KIPS
• /
• 2020.11a
• /
• pp.380-382
• /
• 2020

네트워크에 존재하는 저장 공간을 필요에 따라 유연하게 대여하여 사용할 수 있는 클라우드 스토리지 서비스는 데이터의 일관성 유지, 저렴한 유지관리 비용 등 여러 장점에 힘입어 널리 활용되고 있다. 하지만 클라우드 시스템은 데이터 소유자에 의한 관리가 이루어지지 않으므로 민감한 데이터의 노출에 의한 피해 또한 다수 발생하고 있는데, 이를 해결하기 위하여 암호화 등을 통한 프라이버시 보존을 위한 연구가 꾸준히 진행되고 있다. 본 연구에서는 프라이버시가 보존된 상태에서 클라우드에 저장된 데이터를 검색함에 있어, 대수적 난제에 근거를 둔 접근 제어 기능을 내포한 소프트웨어 기반의 검색 가능한 암호화 (searchable encryption) 기법과 최근 많은 관심을 받고 있는 하드웨어 기반 클라우드 데이터 검색의 효율성 및 기능에 대한 비교 분석을 수행한다. 이를 통하여 하드웨어 기반 기법의 활용을 통한 성능 향상 가능성을 확인하고 잠재적 보안 위협을 검토한다.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.5
• /
• pp.35-44
• /
• 2009

To protect sensitive personal information, data will be stored in encrypted form. However in order to retrieve these encrypted data without decryption, there need efficient search methods to enable the retrieval of the encrypted data. Until now, a number of searchable encryption schemes have been proposed but these schemes are not suitable when dynamic users who have the permission to access the data share the encrypted data. Since, in previous searchable encryption schemes, only specific user who is the data owner in symmetric key settings or has the secret key corresponding to the public key for the encrypted data in asymmetric key settings can access to the encrypted data. To solve this problem, Stephen S. Yau et al. firstly proposed the controlled privacy preserving keyword search scheme which can control the search capabilities of users according to access policies of the data provider. However, this scheme has the problem that the privacy of the data retrievers can be breached. In this paper, we firstly analyze the weakness of Stephen S. Yau et al.'s scheme and propose privacy preserving keyword search with access control. Our proposed scheme preserves the privacy of data retrievers.

• Journal of Internet Computing and Services
• /
• v.24 no.5
• /
• pp.85-96
• /
• 2023

With advance of cloud computing technology, Blockchain as a Service of Cloud Service Provider has been utilized in various areas such as e-Commerce and financial companies to manage customer history and distribution history. However, if users' search history, purchase history, etc. are to be utilized in a BaaS in areas such as recommendation algorithms and search engine development, the users' search queries will be exposed to the company operating the BaaS, and privacy issues will be occured. Z. Guan et al. ensure the unlinkability between users' search query and search result using searchable encryption, and based on the inner product similarity, they select Top-k results that are highly relevant to the users' search query. However, there is a problem that the Top-k results selection may be not possible due to ties of inner product similarity, and BaaS over cloud is not considered. Therefore, this paper solve the problem of Z. Guan et al. using cosine similarity, so we improve accuracy of search result. And based on this, we design a BaaS with secure Top-k search that improved accuracy. Furthermore, we design a smart contracts that preserve privacy of users' search and obtain Top-k search results that are highly relevant to the users' search.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.3
• /
• pp.1229-1248
• /
• 2016

With the feature of convenience and low cost, remote healthcare monitoring (RHM) has been extensively used in modern disease management to improve the quality of life. Due to the privacy of health data, it is of great importance to implement RHM based on a secure and dependable network. However, the network connectivity of existing RHM systems is unreliable in disaster area because of the unforeseeable damage to the communication infrastructure. To design a secure RHM system in disaster area, this paper presents a Secure VANET-Assisted Remote Healthcare Monitoring System (SVC) by utilizing the unique "store-carry-forward" transmission mode of vehicular ad hoc network (VANET). To improve the network performance, the VANET in SVC is designed to be a two-level network consisting of two kinds of vehicles. Specially, an innovative two-level key management model by mixing certificate-based cryptography and ID-based cryptography is customized to manage the trust of vehicles. In addition, the strong privacy of the health information including context privacy is taken into account in our scheme by combining searchable public-key encryption and broadcast techniques. Finally, comprehensive security and performance analysis demonstrate the scheme is secure and efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.5171-5189
• /
• 2016

With the popularity of cloud computing, many data owners outsource their graph data to the cloud for cost savings. The cloud server is not fully trusted and always wants to learn the owners' contents. To protect the information hiding, the graph data have to be encrypted before outsourcing to the cloud. The adjacent vertex search is a very common operation, many other operations can be built based on the adjacent vertex search. A boolean adjacent vertex search is an important basic operation, a query user can get the boolean search results. Due to the graph data being encrypted on the cloud server, a boolean adjacent vertex search is a quite difficult task. In this paper, we propose a solution to perform the boolean adjacent vertex search over encrypted graph data in cloud computing (BASG), which maintains the query tokens and search results privacy. We use the Gram-Schmidt algorithm and achieve the boolean expression search in our paper. We formally analyze the security of our scheme, and the query user can handily get the boolean search results by this scheme. The experiment results with a real graph data set demonstrate the efficiency of our scheme.

• Journal of KIISE
• /
• v.44 no.10
• /
• pp.1112-1123
• /
• 2017

As content providers further offload content-centric services to the cloud, data retrieval over the cloud typically results in many redundant items because there is a prevalent near-duplication of content on the Internet. Simply fetching all data from the cloud severely degrades efficiency in terms of resource utilization and bandwidth, and data can be encrypted by multiple content providers under different keys to preserve privacy. Thus, locating near-duplicate data in a privacy-preserving way is highly dependent on the ability to deduplicate redundant search results and returns best matches without decrypting data. To this end, we propose an efficient near-duplicate detection scheme for encrypted data in the cloud. Our scheme has the following benefits. First, a single query is enough to locate near-duplicate data even if they are encrypted under different keys of multiple content providers. Second, storage, computation and communication costs are alleviated compared to existing schemes, while achieving the same level of search accuracy. Third, scalability is significantly improved as a result of a novel and efficient two-round detection to locate near-duplicate candidates over large quantities of data in the cloud. An experimental analysis with real-world data demonstrates the applicability of the proposed scheme to a practical cloud system. Last, the proposed scheme is an average of 70.6% faster than an existing scheme.